The Hidden Curriculum of a Teacher Induction Program: Ontario Teacher Educators' Perspectives.
Bibliographic record
Abstract
This article investigates the hidden curriculum of Ontario’s New Teacher Induction Program (NTIP). The study involved interviews with 47 teacher educators from eight faculties of education. Responses revealed concerns about (a) who chooses the men‐ tors, (b) the probationary status of new teachers, and (c) the evaluation of new teach‐ ers’ competence. In the opinion of some teacher educators, the structure of NTIP may discourage new teachers from critiquing the system that employs them thus decreas‐ ing the likelihood of their taking a critical democratic stance in their teaching. These findings have implications for any induction or mentorship program for new teach‐ ers. Key Words: teacher education, mentorship, social justice, critical democratic, Ontario New Teacher Induction Program Cet article porte sur les objectifs cachés du Programme dʹinsertion professionnelle du nouveau personnel enseignant (PIPNPE) de l’Ontario. Pour cette recherche, les au‐ teurs ont interviewé 47 professeurs de pédagogie dans huit facultés d’éducation. Ces entrevues révèlent des inquiétudes au sujet (a) du mode de sélection des mentors, (b) du statut probatoire du nouveau personnel enseignant, (c) de l’évaluation des compé‐ tences du nouveau personnel enseignant. Selon certains des répondants, la structure du PIPNPE peut dissuader certains nouveaux enseignants de critiquer le système qui les emploie, ce qui diminue les chances qu’ils prennent une orientation démocratique critique dans leur enseignement. Ces observations ont des implications pour tout programme d’insertion professionnelle ou de mentorat s’adressant au nouveau per‐ sonnel enseignant. Mots clés : formation à l’enseignement, mentorat, justice sociale, critique, démocrati‐ que, Programme dʹinsertion professionnelle du nouveau personnel enseignant de l’Ontario.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".